In the context of the COVID-19 outbreak in a global scenario, mandatory mask-wearing and temperature control can effectively prevent its spread and realize self-protection. Therefore, real-time face-mask wearing and temperature measurement technology is of greater importance against the background of infectious disease prevention and control. The present study adopted MobileNet as the backbone of the single-stage RetinaFace framework for real-time face detection and mask-wearing detection. Moreover, the focal loss function of
Chun-Liang Tung, Ching-Hsin Wang, Yong-Lin Su, "Real-time Face Mask-Wearing Detection and Temperature Measurement based on a Deep Learning Model" in Journal of Imaging Science and Technology, 2022, pp 010403-1 - 010403-10, https://doi.org/10.2352/J.ImagingSci.Technol.2022.66.1.010403